Shirshanka Das is a principal staff software engineer and the architect for LinkedIn’s analytics platforms and applications team. He was among the original authors of a variety of open and closed source projects built at LinkedIn, including Databus, Espresso, and Apache Helix. He is currently working with his team to simplify the big data analytics space at LinkedIn through a multitude of mostly open source projects, including Pinot, a high-performance distributed OLAP engine, Gobblin, a data lifecycle management platform for Hadoop, WhereHows, a data discovery and lineage platform, and Dali, a data virtualization layer for Hadoop.

LinkedIn houses the most valuable professional data in the world. Protecting the privacy of member data has always been paramount. Shirshanka Das and Tushar Shanbhag outline three foundational building blocks for scalable data management that can meet data compliance regulations: a central metadata system, an integrated data movement framework, and a unified data access layer.
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